An increasing number of operations within a data center consist of distributed data processing across multiple computing systems. In particular, an organization may implement multiple computing systems to maintain and process large data sets, wherein data objects from the data sets may be distributed to the computing systems to process the objects in parallel. These objects may include text files, images, videos, spreadsheets, or some other similar type of data object. However, while multiple computing systems may provide efficiency in the parallel processing of large data sets, difficulties often arise in determining the number of computing systems that are required to provide the desired operation. For example, an organization may not employ enough computing systems to process a data set within a required time period. Similarly, an organization may execute too many computing systems to process a data set, which causes power and hardware inefficiencies for the organization, leading to increased operating costs.